---
title: Features and Specifications
description: For those already familiar with LLM application tech stacks, this document serves as a shortcut to understand Dify's unique advantages
---


We adopt transparent policies around product specifications to ensure decisions are made based on complete understanding. Such transparency not only benefits your technical selection, but also promotes deeper comprehension within the community for active contributions.

### Project Basics

<table>
  <thead>
    <tr>
      <th>Attribute</th>
      <th>Details</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <td>Established</td>
      <td>March 2023</td>
    </tr>
    <tr>
      <td>Open Source License</td>
      <td>[Apache License 2.0 with commercial licensing](../../policies/open-source)</td>
    </tr>
    <tr>
      <td>Official R&D Team</td>
      <td>Over 15 full-time employees</td>
    </tr>
    <tr>
      <td>Community Contributors</td>
      <td>Over [290](https://ossinsight.io/analyze/langgenius/dify#overview) people (As of Q2 2024)</td>
    </tr>
    <tr>
      <td>Backend Technology</td>
      <td>Python/Flask/PostgreSQL</td>
    </tr>
    <tr>
      <td>Frontend Technology</td>
      <td>Next.js</td>
    </tr>
    <tr>
      <td>Codebase Size</td>
      <td>Over 130,000 lines</td>
    </tr>
    <tr>
      <td>Release Frequency</td>
      <td>Average once per week</td>
    </tr>
  </tbody>
</table>

### Technical Features

<table>
  <thead>
    <tr>
      <th>Feature</th>
      <th>Details</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <td>LLM Inference Engines</td>
      <td>Dify Runtime (LangChain removed since v0.4)</td>
    </tr>
    <tr>
      <td>Commercial Models Supported</td>
      <td>
        <p><strong>10+</strong>, including OpenAI and Anthropic</p>
        <p>Onboard new mainstream models within 48 hours</p>
      </td>
    </tr>
    <tr>
      <td>MaaS Vendor Supported</td>
      <td><strong>7</strong>, Hugging Face, Replicate, AWS Bedrock, NVIDIA, GroqCloud, together.ai, OpenRouter</td>
    </tr>
    <tr>
      <td>Local Model Inference Runtimes Supported</td>
      <td><strong>6</strong>, Xoribits (recommended), OpenLLM, LocalAI, ChatGLM, Ollama, NVIDIA TIS</td>
    </tr>
    <tr>
      <td>OpenAI Interface Standard Model Integration Supported</td>
      <td><strong>∞</strong></td>
    </tr>
    <tr>
      <td>Multimodal Capabilities</td>
      <td>
        <p>ASR Models</p>
        <p>Rich-text models up to GPT-4o specs</p>
      </td>
    </tr>
    <tr>
      <td>Built-in App Types</td>
      <td>Text generation, Chatbot, Agent, Workflow, Chatflow</td>
    </tr>
    <tr>
      <td>Prompt-as-a-Service Orchestration</td>
      <td>
        <p>Visual orchestration interface widely praised, modify Prompts and preview effects in one place.</p>
        <p><strong>Orchestration Modes</strong></p>
        <ul>
          <li>Simple orchestration</li>
          <li>Assistant orchestration</li>
          <li>Flow orchestration</li>
        </ul>
        <p><strong>Prompt Variable Types</strong></p>
        <ul>
          <li>String</li>
          <li>Radio enum</li>
          <li>External API</li>
          <li>File (Q3 2024)</li>
        </ul>
      </td>
    </tr>
    <tr>
      <td>Agentic Workflow Features</td>
      <td>
        <p>Industry-leading visual workflow orchestration interface, live-editing node debugging, modular DSL, and native code runtime, designed for building more complex, reliable, and stable LLM applications.</p>
        <p><strong>Supported Nodes</strong></p>
        <ul>
          <li>LLM</li>
          <li>Knowledge Retrieval</li>
          <li>Question Classifier</li>
          <li>IF/ELSE</li>
          <li>CODE</li>
          <li>Template</li>
          <li>HTTP Request</li>
          <li>Tool</li>
        </ul>
      </td>
    </tr>
    <tr>
      <td>RAG Features</td>
      <td>
        <p>Industry-first visual knowledge base management interface, supporting snippet previews and recall testing.</p>
        <p><strong>Indexing Methods</strong></p>
        <ul>
          <li>Keywords</li>
          <li>Text vectors</li>
          <li>LLM-assisted question-snippet model</li>
        </ul>
        <p><strong>Retrieval Methods</strong></p>
        <ul>
          <li>Keywords</li>
          <li>Text similarity matching</li>
          <li>Hybrid Search</li>
          <li>N choose 1 (Legacy)</li>
          <li>Multi-path retrieval</li>
        </ul>
        <p><strong>Recall Optimization</strong></p>
        <ul>
          <li>Rerank models</li>
        </ul>
      </td>
    </tr>
    <tr>
      <td>ETL Capabilities</td>
      <td>
        <p>Automated cleaning for TXT, Markdown, PDF, HTML, DOC, CSV formats. Unstructured service enables maximum support.</p>
        <p>Sync Notion docs as knowledge bases.</p>
        <p>Sync Webpages as knowledge bases.</p>
      </td>
    </tr>
    <tr>
      <td>Vector Databases Supported</td>
      <td>Qdrant (recommended), Weaviate, Zilliz/Milvus, Pgvector, Pgvector-rs, Chroma, OpenSearch, TiDB, Tencent Vector, Oracle, Relyt, Analyticdb, Couchbase</td>
    </tr>
    <tr>
      <td>Agent Technologies</td>
      <td>
        <p>ReAct, Function Call.</p>
        <p><strong>Tooling Support</strong></p>
        <ul>
          <li>Invoke OpenAI Plugin standard tools</li>
          <li>Directly load OpenAPI Specification APIs as tools</li>
        </ul>
        <p><strong>Built-in Tools</strong></p>
        <ul>
          <li>40+ tools (As of Q2 2024)</li>
        </ul>
      </td>
    </tr>
    <tr>
      <td>Logging</td>
      <td>Supported, annotations based on logs</td>
    </tr>
    <tr>
      <td>Annotation Reply</td>
      <td>Based on human-annotated Q&As, used for similarity-based replies. Exportable as data format for model fine-tuning.</td>
    </tr>
    <tr>
      <td>Content Moderation</td>
      <td>OpenAI Moderation or external APIs</td>
    </tr>
    <tr>
      <td>Team Collaboration</td>
      <td>Workspaces, multi-member management</td>
    </tr>
    <tr>
      <td>API Specs</td>
      <td>RESTful, most features covered</td>
    </tr>
    <tr>
      <td>Deployment Methods</td>
      <td>Docker, Helm</td>
    </tr>
  </tbody>
</table>

{/*
Contributing Section
DO NOT edit this section!
It will be automatically generated by the script.
*/}

<CardGroup cols="2">
    <Card
        title="Edit this page"
        icon="pen-to-square"
        href="https://github.com/langgenius/dify-docs-mintlify/edit/main/en/getting-started/readme/features-and-specifications.mdx"
    >
        Help improve our documentation by contributing directly
    </Card>
    <Card
        title="Report an issue"
        icon="github"
        href="https://github.com/langgenius/dify-docs-mintlify/issues/new?title=Documentation%20Issue%3A%20res-and-specificati&body=%23%23%20Issue%20Description%0A%3C%21--%20Please%20briefly%20describe%20the%20issue%20you%20found%20--%3E%0A%0A%23%23%20Page%20Link%0Ahttps%3A%2F%2Fgithub.com%2Flanggenius%2Fdify-docs-mintlify%2Fblob%2Fmain%2Fen/getting-started/readme%2Ffeatures-and-specifications.mdx%0A%0A%23%23%20Suggested%20Changes%0A%3C%21--%20If%20you%20have%20specific%20suggestions%20for%20changes%2C%20please%20describe%20them%20here%20--%3E%0A%0A%3C%21--%20Thank%20you%20for%20helping%20improve%20our%20documentation%21%20--%3E"
    >
        Found an error or have suggestions? Let us know
    </Card>
</CardGroup>
